Internet has recently evolved from a traditional human-centric network, which allows users to create and consume information, into an internet of things (IoT) network which allows distributed things to exchange and process information. Further, such IoT technology is now growing into an internet of everything (IoE) technology through a combination of big data processing technology based on a connection with a cloud server or the like. In order to realize IoT or IoE, various related technologies such as sensing technique, infrastructure for wired/wireless communication and network, service interface technique, and security technique are also required. In addition, sensor network technology, machine-to-machine (M2M) technology, machine type communication (MTC) technology, etc. are studied in these days.
In IoT environments, intelligent internet technology services for collecting and analyzing various kinds of data from connected things and then creating a new value to the human life may be provided. Moreover, through convergence and integration between the existing information technology (IT) and several industries, IoT technology may be applied to a great variety of industrial fields such as a smart home, a smart building, a smart city, a smart car or a connected car, a smart grid, a healthcare, smart home appliances, and a high-tech medical service.
Meanwhile, the implementation of IoT technology inherently needs techniques to measure a user location and provide a service on the basis of the user location.
However, typical user proximity sensing techniques based on Bluetooth low energy (BLE) technique requires essentially a BLE device and thus has a drawback of higher initial cost. In addition, although being advantageous to the detection of a user's proximity, the user proximity sensing technique has a relatively low accuracy in measuring a user's location.
Another technique to estimate a terminal's location by measuring a received signal strength indicator (RSSI) of a Wi-Fi signal received from a wireless access point (AP) has an advantage of requiring no additional device such as a BLE device. However, RSSI-based location estimation has a strong possibility of causing errors due to irregular accuracy depending on terminal locations.
Accordingly, a technique to precisely measure a user location and reliably provide a service on the basis of the user location is needed.